Gray's Reinforcement Sensitivity Theory: a psychometric critique

This study identifies valid orthogonal scales of Gray's animal learning paradigms, upon which his Reinforcement Sensitivity Theory (RST) is based, by determining a revised structure to the Gray-Wilson Personality Questionnaire (GWPQ) (Wilson, Gray, & Barrett, 1990). It is also determined how well Gray's RST scales predict the surface scales of personality, which were measured in terms of Eysenck Personality Profiler (EPP) scales, the EPQ-R and the learning styles questionnaire (LSQ) scales. First, results suggest that independent pathways of RST scales may exist in humans. Second, Fight seems related to Anxiety and not the Fight/Flight system as proposed by RST. Third. a remarkably consistent story emerges in that Extraversion scales are predicted by Fight, Psychoticism scales are predicted by Active-avoidance, Fight and/or Flight, and Neuroticism scales tend not to be predicted at all (except for Anxiety). Fourth, Gray's revised scales are Unrelated to gender and age effects and show a predictable overlap with the LSQ and original GWPQ scales. It is concluded that Gray's model of personality might provide a stable biological basis of many surface scales of personality, but that there must also be other influences on personality. These results question the finer structure of Gray's RST whilst also showing that RST has greater range of applicability than a strict interpretation of theory implies. (C) 2002 Elsevier Science Ltd. All rights reserved.

Altered fungal sensitivity to a plant antimicrobial peptide through over-expression of yeast cDNAs

A yeast cDNA expression library was screened to identify genes and cellular processes that influence fungal sensitivity to a plant antimicrobial peptide. A plasmid-based, GAL1 promoter-driven yeast cDNA expression library was introduced into a yeast genotype susceptible to the antimicrobial peptide MiAMP1 purified from Macadamia integrifolia. Following a screen of 20,000 cDNAs, three yeast cDNAs were identified that reproducibly provided transformants with galactose-dependent resistance to MiAMP1. These cDNAs encoded a protein of unknown function, a component (VMA11) of the vacuolar H+-ATPase and a component (cytochrome c oxidase subunit VIa) of the mitochondrial electron transport chain, respectively. To identify genes that increased sensitivity to MiAMP1, the yeast cDNA expression library was introduced into a yeast mutant with increased resistance to MiAMP1. From 11,000 cDNAs screened, two cDNA clones corresponding to a ser/thr kinase and a ser/thr phosphatase reproducibly increased MiAMP1 susceptibility in the mutant in a galactose-dependent manner. Deletion mutants were available for three of the five genes identified but showed no change in their sensitivity to MiAMP1, indicating that these genes could not be detected by screening of yeast deletion mutant libraries. Yeast cDNA expression library screening therefore provides an alternative approach to gene deletion libraries to identify genes that can influence the sensitivity of fungi to plant antimicrobial peptides.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

Accounting for management costs in sensitivity analyses of matrix population models

Traditional sensitivity and elasticity analyses of matrix population models have been used to p inform management decisions, but they ignore the economic costs of manipulating vital rates. For exam le, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously, These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency.